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BACKGROUND: We aimed to identify important components of, and practical resources relevant for inclusion in, a toolkit to aid exercise delivery for people with hip/knee osteoarthritis. METHOD: An online international multi-disciplinary survey was conducted across 43 countries (139 clinicians, 44 people with hip/knee osteoarthritis and 135 osteoarthritis researchers). Participants were presented with the seeding statement 'Practical resources to aid the implementation of exercise for people with hip/knee osteoarthritis should…' and asked to provide up to 10 open text responses. Responses underwent refinement and qualitative content analysis to create domains and categories. RESULTS: Refinement of 551 open text responses yielded 72 unique statements relevant for analysis. Statements were organised into nine broad domains, suggesting that resources to aid exercise delivery should: (1) be easily accessible; (2) be of high quality; (3) be developed by, and for, stakeholders; (4) include different ways of delivering information; (5) include different types of resources to support exercise and non-exercise components of self-management; (6) include resources on recommended exercises and how to perform/progress them; (7) include tools to support motivation and track progress; (8) include resources to enable tailoring of the programme to the individual and; (9) facilitate access to professional and peer support. CONCLUSION: Our findings identified important components of, and practical resources to include within, a toolkit to aid delivery of exercise for people with hip/knee osteoarthritis. These findings have implications for exercise providers and lay the foundation for the development of a toolkit to help ensure exercise provision aligns with current international recommendations.

OBJECTIVE: To develop evidence-informed recommendations to support the delivery of best practice therapeutic exercise for people with knee and/or hip osteoarthritis (OA). DESIGN: A multi-stage, evidence-informed, international multi-disciplinary consensus process that included: 1) a narrative literature review to synthesise existing evidence; 2) generation of evidence-informed proposition statements about delivery of exercise for people with knee and/or hip OA by an international multi-disciplinary expert panel, with statements refined and analysed thematically; 3) an e-Delphi survey with the expert panel to gain consensus on the most important statements; 4) a final round of statement refinement and thematic analysis to group remaining statements into domains. RESULTS: The expert panel included 318 members (academics, health care professionals and exercise providers, patient representatives) from 43 countries. Final recommendations comprised 54 specific proposition statements across 11 broad domains: 1) use an evidence-based approach; 2) consider exercise in the context of living with OA and pain; 3) undertake a comprehensive baseline assessment with follow-up; 4) set goals; 5) consider the type of exercise; 6) consider the dose of exercise; 7) modify and progress exercise; 8) individualise exercise; 9) optimise the delivery of exercise; 10) focus on exercise adherence; and 11) provide education about OA and the role of exercise. CONCLUSION: The breadth of issues identified as important by the international diverse expert panel highlights that delivering therapeutic exercise for OA is multi-dimensional and complex.

Objectives: Osteoarthritis (OA) patient stratification is an important challenge to design tailored treatments and drive drug development. Biochemical markers reflecting joint tissue turnover were measured in the IMI-APPROACH cohort at baseline and analysed using a machine learning approach in order to study OA-dominant phenotypes driven by the endotype-related clusters and discover the driving features and their disease-context meaning. Methods: Data quality assessment was performed to design appropriate data preprocessing techniques. The k-means clustering algorithm was used to find dominant subgroups of patients based on the biochemical markers data. Classification models were trained to predict cluster membership, and Explainable AI techniques were used to interpret these to reveal the driving factors behind each cluster and identify phenotypes. Statistical analysis was performed to compare differences between clusters with respect to other markers in the IMI-APPROACH cohort and the longitudinal disease progression. Results: Three dominant endotypes were found, associated with three phenotypes: C1) low tissue turnover (low repair and articular cartilage/subchondral bone turnover), C2) structural damage (high bone formation/resorption, cartilage degradation) and C3) systemic inflammation (joint tissue degradation, inflammation, cartilage degradation). The method achieved consistent results in the FNIH/OAI cohort. C1 had the highest proportion of non-progressors. C2 was mostly linked to longitudinal structural progression, and C3 was linked to sustained or progressive pain. Conclusions: This work supports the existence of differential phenotypes in OA. The biomarker approach could potentially drive stratification for OA clinical trials and contribute to precision medicine strategies for OA progression in the future.